[transformer] fix warning: ignore(True) has been deprecated (#2492)

* [transformer] fix warning: ignore(True) has been deprecated * [transformer] fix warning: ignore(True) has been deprecated
wenet-e2e · Apr 18, 2024 · 5b4e2f4 · 5b4e2f4
1 parent 69a084f
commit 5b4e2f4
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Showing 9 changed files with 15 additions and 15 deletions.
diff --git a/wenet/ctl_model/asr_model_ctl.py b/wenet/ctl_model/asr_model_ctl.py
@@ -67,7 +67,7 @@ def __init__(
         self.ctl_weight = ctl_weight
         self.logit_temp = logit_temp
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward(
         self,
         batch: dict,

diff --git a/wenet/k2/model.py b/wenet/k2/model.py
@@ -54,7 +54,7 @@ def __init__(
         if self.lfmmi_dir != '':
             self.load_lfmmi_resource()
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def _forward_ctc(
             self, encoder_out: torch.Tensor, encoder_mask: torch.Tensor,
             text: torch.Tensor,
@@ -63,7 +63,7 @@ def _forward_ctc(
                                                     text)
         return loss_ctc, ctc_probs
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def load_lfmmi_resource(self):
         try:
             import icefall
@@ -94,7 +94,7 @@ def load_lfmmi_resource(self):
                 assert len(arr) == 2
                 self.word_table[int(arr[1])] = arr[0]
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def _calc_lfmmi_loss(self, encoder_out, encoder_mask, text):
         try:
             import k2

diff --git a/wenet/paraformer/layers.py b/wenet/paraformer/layers.py
@@ -282,7 +282,7 @@ def forward_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,
             xs, _, _, _ = layer(xs, chunk_masks, pos_emb, mask_pad)
         return xs
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward_layers_checkpointed(self, xs: torch.Tensor,
                                     chunk_masks: torch.Tensor,
                                     pos_emb: torch.Tensor,
@@ -471,7 +471,7 @@ def forward_layers(self, x: torch.Tensor, tgt_mask: torch.Tensor,
             x = layer(x)
         return x
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward_layers_checkpointed(self, x: torch.Tensor,
                                     tgt_mask: torch.Tensor,
                                     memory: torch.Tensor,

diff --git a/wenet/paraformer/paraformer.py b/wenet/paraformer/paraformer.py
@@ -148,7 +148,7 @@ def __init__(self,
         #    labels:     你 好 we@@ net eos
         self.add_eos = add_eos
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward(
         self,
         batch: Dict,
@@ -232,7 +232,7 @@ def _calc_att_loss(
                               ignore_label=self.ignore_id)
         return loss_att, acc_att
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def _sampler(self, encoder_out, encoder_out_mask, ys_pad, ys_pad_lens,
                  pre_acoustic_embeds):
         device = encoder_out.device

diff --git a/wenet/ssl/w2vbert/w2vbert_model.py b/wenet/ssl/w2vbert/w2vbert_model.py
@@ -158,7 +158,7 @@ def _reset_parameter(module: torch.nn.Module):
                 _reset_parameter(conv1)
                 _reset_parameter(conv2)
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward(
         self,
         batch: Dict,

diff --git a/wenet/ssl/wav2vec2/wav2vec2_model.py b/wenet/ssl/wav2vec2/wav2vec2_model.py
@@ -217,7 +217,7 @@ def _reset_parameter(module: torch.nn.Module):
                 _reset_parameter(conv1)
                 _reset_parameter(conv2)
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward(
         self,
         batch: Dict,

diff --git a/wenet/transformer/asr_model.py b/wenet/transformer/asr_model.py
@@ -74,7 +74,7 @@ def __init__(
             normalize_length=length_normalized_loss,
         )
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward(
         self,
         batch: dict,
@@ -133,7 +133,7 @@ def forward(
             "th_accuracy": acc_att,
         }
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def _forward_ctc(
             self, encoder_out: torch.Tensor, encoder_mask: torch.Tensor,
             text: torch.Tensor,
@@ -231,7 +231,7 @@ def _forward_encoder(
             )  # (B, maxlen, encoder_dim)
         return encoder_out, encoder_mask
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def ctc_logprobs(self,
                      encoder_out: torch.Tensor,
                      blank_penalty: float = 0.0,

diff --git a/wenet/transformer/decoder.py b/wenet/transformer/decoder.py
@@ -207,7 +207,7 @@ def forward_layers(self, x: torch.Tensor, tgt_mask: torch.Tensor,
                                                      memory_mask)
         return x
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward_layers_checkpointed(self, x: torch.Tensor,
                                     tgt_mask: torch.Tensor,
                                     memory: torch.Tensor,

diff --git a/wenet/transformer/encoder.py b/wenet/transformer/encoder.py
@@ -184,7 +184,7 @@ def forward_layers(self, xs: torch.Tensor, chunk_masks: torch.Tensor,
             xs, chunk_masks, _, _ = layer(xs, chunk_masks, pos_emb, mask_pad)
         return xs
 
-    @torch.jit.ignore(drop=True)
+    @torch.jit.unused
     def forward_layers_checkpointed(self, xs: torch.Tensor,
                                     chunk_masks: torch.Tensor,
                                     pos_emb: torch.Tensor,